Cluster Analysis Identified Clinically Relevant Metabolic Syndrome Endophenotypes

Abstract

Aims/hypothesis Metabolic syndrome (MetS) is a collection of cardiovascular risk factors; however, the high prevalence and heterogeneity impede proper and effective clinical management of MetS. In order for precision medicine to work for MetS, we aimed to identify clinically relevant MetS sub-phenotypes. Methods We conducted cluster analysis on individuals from UK Biobank based on MetS criteria to reveal endophenotypes, identified the corresponding cardiometabolic traits and established the association across 21 clinical outcomes. Genome-wide association studies were conducted to identify associated genotypic traits. We further compared the genotypic traits to reveal endophenotypes-specific genotypic traits. Lastly, potential drug targets were identified for the different endophenotypes. Results Five MetS subgroups were identified which were Cluster 1 (C1): non-descriptive, Cluster 2 (C2): hypertensive, Cluster 3 (C3): obese, Cluster 4 (C4): lipodystrophy-like, and Cluster 5 (C5): hyperglycaemic. Some MetS clusters had higher CVD risks such as C1 (OR=6.765) and C5 (OR=9.486). Despite being non-descriptive across all cardiometabolic traits, C1 had higher risks for most clinical outcomes. MetS clusters also had different risks to various types of cancers. GWAS of each MetS clusters revealed different genotypic traits. LPCAT2 was associated with all clusters except C2 and expression is specific to immune cells. C1 GWAS revealed novel findings of TRIM63, MYBPC3, MYLPF, and RAPSN. Intriguingly, C1, C3, and C4 were associated with genes highly expressed in brain tissues: CN1H2, TMEM151A, MT3, and C1QTNF4. The cluster-specific genotypic traits also revealed potential drug repurposing targets specific to the endophenotypes. Conclusion/interpretation MetS is highly heterogeneous with endophenotypes that are different in terms of phenotypic and genotypic traits. GWAS of subgroups revealed novel cardiometabolic genotypes which were masked by heterogeneity of MetS.